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Find entity mentions

find_mentions
Read-onlyIdempotent

Locate recorded mentions of an indexed entity across saved items, returning stored spans, timestamps, and source links. Use for people, products, tools, or topics already indexed as entities.

Instructions

Find recorded entity-name mentions across saved items, with stored spans, timing and source links. Use for people, products, tools or topics already indexed as entities; use search_clips for arbitrary transcript text or search_uoinks for whole-item search. Ranks by name match with newest first on ties. Results are limited and do not extract new entities.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum rows to return in this response; does not change stored data.
matchNoForgiving matches entity name words; strict requires the exact normalized name.forgiving
entityYesEntity name to look up (case-insensitive).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.12.1

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile needs no restating. The description usefully adds ranking behavior (name match, newest first on ties) and the constraint that results are limited and no new entities are extracted. However 'results are limited' never quantifies the cap or suggests how to page, which is the one behavioral fact an agent would still want.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four compact sentences, all front-loaded with the core purpose first and routing second, and every sentence carries distinct information. Minor deductions for the typo 'search_uoinks' and for packing ranking plus result limits into terse trailing statements that read slightly like afterthoughts.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries return-shape burden and does name the salient fields (spans, timing, source links) plus ordering and result limits. The unquantified result cap and the absence of any guidance on narrowing via the match parameter leave a small but real gap for a lookup tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all three parameters — entity, limit and the forgiving/strict match enum — are already documented in the schema. The description mentions name matching in the ranking sentence but adds no syntax, normalization or scope detail beyond what the schema provides; baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Find recorded entity-name mentions across saved items') and adds the return shape agents care about: stored spans, timing and source links. It explicitly distinguishes itself from search_clips (arbitrary transcript text) and search_uoinks (whole-item search), so an agent can pick without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives both positive guidance ('use for people, products, tools or topics already indexed as entities') and negative guidance ('do not extract new entities'), plus two named alternatives with the condition that selects them. Nothing is left to inference about when to pick a different tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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